Package com.google.cloud.aiplatform.v1beta1

Class ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

java.lang.Object

com.google.protobuf.AbstractMessageLite.Builder

com.google.protobuf.AbstractMessage.Builder<BuilderT>

com.google.protobuf.GeneratedMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>

com.google.cloud.aiplatform.v1beta1.ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

All Implemented Interfaces:

ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable

Enclosing class:

ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue

public static final class ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
extends com.google.protobuf.GeneratedMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>
implements ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder

 Summary statistics for a population of values.
 

Protobuf type google.cloud.aiplatform.v1beta1.ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue

Method Summary

Modifier and Type	Method	Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue	build()
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue	buildPartial()
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	clear()
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	clearDistribution()	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	clearDistributionDeviation()	Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue	getDefaultInstanceForType()
static final com.google.protobuf.Descriptors.Descriptor	getDescriptor()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType()
com.google.protobuf.Value	getDistribution()	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
com.google.protobuf.Value.Builder	getDistributionBuilder()	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
double	getDistributionDeviation()	Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics
com.google.protobuf.ValueOrBuilder	getDistributionOrBuilder()	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
boolean	hasDistribution()	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable	internalGetFieldAccessorTable()
final boolean	isInitialized()
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	mergeDistribution(com.google.protobuf.Value value)	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	mergeFrom(ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue other)
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	mergeFrom(com.google.protobuf.Message other)
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	setDistribution(com.google.protobuf.Value value)	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	setDistribution(com.google.protobuf.Value.Builder builderForValue)	Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder	setDistributionDeviation(double value)	Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics

Methods inherited from class com.google.protobuf.GeneratedMessage.Builder

addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3

Methods inherited from class com.google.protobuf.AbstractMessage.Builder

findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class com.google.protobuf.AbstractMessageLite.Builder

addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageException

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.google.protobuf.Message.Builder

mergeDelimitedFrom, mergeDelimitedFrom

Methods inherited from interface com.google.protobuf.MessageLite.Builder

mergeFrom

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Method Details

getDescriptor

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

internalGetFieldAccessorTable

protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()

Specified by:

internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>

clear

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clear()

Specified by:

clear in interface com.google.protobuf.Message.Builder

Specified by:

clear in interface com.google.protobuf.MessageLite.Builder

Overrides:

clear in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>

getDescriptorForType

public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()

Specified by:

getDescriptorForType in interface com.google.protobuf.Message.Builder

Specified by:

getDescriptorForType in interface com.google.protobuf.MessageOrBuilder

Overrides:

getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>

getDefaultInstanceForType

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue getDefaultInstanceForType()

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

build

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue build()

Specified by:

build in interface com.google.protobuf.Message.Builder

Specified by:

build in interface com.google.protobuf.MessageLite.Builder

buildPartial

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue buildPartial()

Specified by:

buildPartial in interface com.google.protobuf.Message.Builder

Specified by:

buildPartial in interface com.google.protobuf.MessageLite.Builder

mergeFrom

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(com.google.protobuf.Message other)

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>

mergeFrom

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue other)

isInitialized

public final boolean isInitialized()

Specified by:

isInitialized in interface com.google.protobuf.MessageLiteOrBuilder

Overrides:

isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>

mergeFrom

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(com.google.protobuf.CodedInputStream input,
 com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                                                                 throws IOException

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Specified by:

mergeFrom in interface com.google.protobuf.MessageLite.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder>

Throws:

IOException

hasDistribution

public boolean hasDistribution()

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

Specified by:

hasDistribution in interface ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder

Returns:

Whether the distribution field is set.

getDistribution

public com.google.protobuf.Value getDistribution()

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

Specified by:

getDistribution in interface ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder

Returns:

The distribution.

setDistribution

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistribution(com.google.protobuf.Value value)

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

setDistribution

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistribution(com.google.protobuf.Value.Builder builderForValue)

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

mergeDistribution

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeDistribution(com.google.protobuf.Value value)

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

clearDistribution

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearDistribution()

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

getDistributionBuilder

public com.google.protobuf.Value.Builder getDistributionBuilder()

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

getDistributionOrBuilder

public com.google.protobuf.ValueOrBuilder getDistributionOrBuilder()

 Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
 

.google.protobuf.Value distribution = 1;

Specified by:

getDistributionOrBuilder in interface ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder

getDistributionDeviation

public double getDistributionDeviation()

 Distribution distance deviation from the current dataset's statistics
 to baseline dataset's statistics.
 * For categorical feature, the distribution distance is calculated
 by L-inifinity norm or Jensen–Shannon divergence.
 * For numerical feature, the distribution distance is calculated by
 Jensen–Shannon divergence.
 

double distribution_deviation = 2;

Specified by:

getDistributionDeviation in interface ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder

Returns:

The distributionDeviation.

setDistributionDeviation

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistributionDeviation(double value)

 Distribution distance deviation from the current dataset's statistics
 to baseline dataset's statistics.
 * For categorical feature, the distribution distance is calculated
 by L-inifinity norm or Jensen–Shannon divergence.
 * For numerical feature, the distribution distance is calculated by
 Jensen–Shannon divergence.
 

double distribution_deviation = 2;

Parameters:

value - The distributionDeviation to set.

Returns:

This builder for chaining.

clearDistributionDeviation

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearDistributionDeviation()

 Distribution distance deviation from the current dataset's statistics
 to baseline dataset's statistics.
 * For categorical feature, the distribution distance is calculated
 by L-inifinity norm or Jensen–Shannon divergence.
 * For numerical feature, the distribution distance is calculated by
 Jensen–Shannon divergence.
 

double distribution_deviation = 2;

Returns:

This builder for chaining.